The purposes of this research are to grasp characteristics of solutions of flow-demand facility location models, and to analyze the effect of fast transportation routes on the location of urban facilities and urban spatial structure.First, we focused a facility location model assuming that demand for service originates from users traveling, which is not directly for the purpose of obtaining the service, as is seen in actual behavior. We combine such a flow-demand location model and the traditional p-median model. Effect of change in jobs-housing spatial structure on optimal facility location is analyzed considering two types of demand : commuting-based demand and home-based demand. With some examples on an ideal triangular lattice urban network, it is shown that facility location decentralizes toward outer suburbs as spatial correlation of home and workplaces gets stronger or as home-based demand gets more dominant.Second, we treated a flow-demand facility location model that minimizes
… More not only total travel distance but also necessary flow for given amounts of trip generation and termination. The proposed model is based on a traditional transportation model as well as a p-median model for flow-demand, and can be solved by mixed integer programming technique. By applying the flow-minimizing flow-demand location model to Tokyo metropolitan area, we find that a larger number of users is seen at facilities in the city centers than at facilities in peripheral areas. Optimal location has intermediate pattern of p-median results for origin-based demand and for destination-based demand. Capacity constraint enforces concentration of terminal facilities at city centers.Third, we dealt with effect of fast transportation routes on optimal facility location and urban spatial structure. Rapid transportation network has an influence on the distribution of transportation flow by distorting urban space. Flow-demand facility location models with fast transportation routes bring about spatial hierarchy of urban structure. Less